Ground moving target detection and feature extraction with airborne phased array radar.

摘要

“Battlefield awareness” is critical to the success of future military operations. Enabling radar signal processing techniques for battlefield awareness includes the detection and recognition of ground moving targets. Since the Gulf War, DARPA (Defence Advanced Research Projects Agency) has initiated several programs to improve the detection and recognition capability of existing systems, including MSTAR (Moving and Stationary Target Acquisition and Recognition), MTE (Moving Target Exploitation), and SHARP (System-oriented HRR Automatic Recognition Program). Our efforts herein are partially funded by one of the DARPA programs. In this dissertation, we investigate the detection and feature extraction of ground moving targets with airborne phased array radar.; The ground clutter observed by an airborne radar is spread over both the range and spatial angle. The clutter spectrum also covers a certain Doppler region due to the platform motion. Without clutter suppression, moving target detection and parameter estimation are impossible. For airborne low range resolution (LRR) phased array radar, we demonstrate that the combination of a vector auto-regressive (VAR) filtering technique and a maximum likelihood (ML) parameter estimation method is an effective approach for carrying out clutter suppression and parameter estimation, and being more robust against system mismatches than conventional displaced-phase-center-antenna (DPCA) processing.; Compared to a conventional airborne LRR radar, an airborne High Range Resolution (HRR) radar can not only enhance the radar's capability of detecting, locating and tracking moving targets, but can also provide valuable features for applications including automatic target recognition (ATR). We study moving target feature extraction algorithms in the presence of ground clutter for airborne HRR phased array radar. The VAR filtering technique is extended for airborne HRR phased array radar for clutter suppression. We also devise effective and robust feature extraction algorithms for the radar system.; Multiple moving target scenarios occur frequently in radar applications. Yet, to the best of our knowledge, little research on the topic has been reported in the literature. We present a relaxation-based algorithm for multiple moving target feature extraction, which reduces the multiple moving target feature extraction problem to a sequence of single moving target feature extraction problems.; Target detection is critical for every radar system since without target detection, target feature extraction and ATR are impossible. Our final discussion is focused on multiple moving target detection for airborne HRR phased array radar. We combine the multiple moving target feature extraction methods with a single moving target detection algorithm for multiple target detection.; Finally, the VAR filtering technique is demonstrated to be effective for clutter suppression via numerical examples. The proposed moving target detection and feature extraction algorithms are also shown to be both robust and accurate.